Transient functioning mode of manufacturing systems with operation time constraints

1998 ◽  
Vol 14 (10) ◽  
pp. 694-703 ◽  
Author(s):  
S. Calvez ◽  
P. Aygalinc ◽  
P. Bonhomme
Keyword(s):  
Manufacturing Systems ◽  
Operation Time ◽  
Time Constraints

scholarly journals Multimodal processes prototyping subject to grid-like network and fuzzy operation time constraints

2017 ◽  
Vol 273 (1-2) ◽  
pp. 561-585 ◽  
Author(s):  
Grzegorz Bocewicz ◽  
Zbigniew Banaszak ◽  
Izabela Nielsen
Keyword(s):  
Operation Time ◽  
Time Constraints

P-Time Petri Nets for Manufacturing Systems with Staying Time Constraints

1997 ◽  
Vol 30 (6) ◽  
pp. 1487-1492 ◽  
Author(s):  
Soizick Calvez ◽  
Pascal Aygalinc ◽  
Wael Khansa
Keyword(s):  
Petri Nets ◽  
Manufacturing Systems ◽  
Time Constraints ◽  
Time Petri Nets ◽  
Staying Time

Smoothing Disturbances in Manufacturing Systems with Shelf Time Constraints

1997 ◽  
Vol 30 (19) ◽  
pp. 43-48
Author(s):  
Pascal Aygalinc ◽  
Soizick Calvez ◽  
Simon Collart-Dutilleul ◽  
Wael Khansa
Keyword(s):  
Manufacturing Systems ◽  
Time Constraints

scholarly journals Fuzzy Filtering of Sensors Signals in Manufacturing Systems with Time Constraints

2010 ◽  
Vol 5 (3) ◽  
pp. 362 ◽  
Author(s):  
Anis M’halla ◽  
Nabil Jerbi ◽  
Simon Collart Dutilleul ◽  
Etienne Craye ◽  
Mohamed Benrejeb
Keyword(s):  
Fuzzy Systems ◽  
Manufacturing Systems ◽  
Knowledge Integration ◽  
Expert Knowledge ◽  
Time Constraints ◽  
Quality And Safety ◽  
Job Shops ◽  
New Approach ◽  
Robustness Property ◽  
Filtering Approach

The presented work is dedicated to the supervision of manufacturing job-shops with time constraints. Such systems have a robustness property towards time disturbances. The main contribution of this paper is a fuzzy filtering approach of sensors signals integrating the robustness values. This new approach integrates a classic filtering mechanism of sensors signals and fuzzy logic techniques. The strengths of these both techniques are taken advantage of the avoidance of control freezing and the capability of fuzzy systems to deal with imprecise information by using fuzzy rules. Finally, to demonstrate the effectiveness and accuracy of this new approach, an example is depicted. The results show that the fuzzy approach allows keeping on producing, but in a degraded mode, while providing the guarantees of quality and safety based on expert knowledge integration.

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